On Thu, 04 Jan 2007 21:37:08 -0600
Robert Kern <robert.kern at gmail.com> wrote:
> Alan Jackson wrote:
> > I've been working with numnpy (Numeric actually, we're a little behind), in a
> > framework that requires that we allow for NaN's to appear at random in our
> > arrays. We have handled that with masked arrays, but I am finding those
> > somewhat awkward to work with, and given that the NaN's will normally be
> > rare, it seems a shame to double the storage costs that way.
> >
> > Any suggestions for a better overall strategy for dealing with NaN's?
>> It depends. What do you want to do with them? Why do they show up in your data?
> I.e. is your framework using them to represent missing data? or are they simply
> showing up from computations (0/0)?
Missing data. Basically want to handle missing data as painlessly as possible
without having to add a bunch of stuff every time a calculation is done.
>> --
> Robert Kern
>> "I have come to believe that the whole world is an enigma, a harmless enigma
> that is made terrible by our own mad attempt to interpret it as though it had
> an underlying truth."
> -- Umberto Eco
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|alan at ajackson.org | And a Heaven in a Wild Flower, |
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